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openai中國(guó)可以用嗎(中國(guó)怎么用opensea)
大家好!今天讓創(chuàng)意嶺的小編來(lái)大家介紹下關(guān)于openai中國(guó)可以用嗎的問(wèn)題,以下是小編對(duì)此問(wèn)題的歸納整理,讓我們一起來(lái)看看吧。
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官網(wǎng):https://ai.de1919.com
本文目錄:
一、開(kāi)放api是開(kāi)源嗎
開(kāi)放API并不等同于開(kāi)源。開(kāi)放API是指一個(gè)軟件或平臺(tái)允許第三方開(kāi)發(fā)者使用其接口和數(shù)據(jù),以便創(chuàng)建新的應(yīng)用程序或服務(wù)。開(kāi)源則是指軟件的源代碼是公開(kāi)的,任何人都可以查看、修改和分發(fā)。雖然開(kāi)放API和開(kāi)源都可以促進(jìn)創(chuàng)新和合作,但它們是不同的概念。
開(kāi)放API的優(yōu)點(diǎn)是可以讓不同的應(yīng)用程序之間實(shí)現(xiàn)互操作性,從而提高整個(gè)生態(tài)系統(tǒng)的價(jià)值。例如,許多社交媒體平臺(tái)都提供開(kāi)放API,使得第三方開(kāi)發(fā)者可以創(chuàng)建各種應(yīng)用程序,如社交媒體管理工具、數(shù)據(jù)分析工具等。這些應(yīng)用程序可以幫助用戶更好地管理和分析他們的社交媒體賬戶,從而提高效率和效果。
總之,開(kāi)放API和開(kāi)源是兩個(gè)不同的概念,但它們都可以促進(jìn)創(chuàng)新和合作。開(kāi)放API可以讓不同的應(yīng)用程序之間實(shí)現(xiàn)互操作性,從而提高整個(gè)生態(tài)系統(tǒng)的價(jià)值。而開(kāi)源則可以讓開(kāi)發(fā)者更容易地查看、修改和分發(fā)軟件的源代碼,從而促進(jìn)創(chuàng)新和合作。
二、openai能當(dāng)爬蟲(chóng)使嗎
你好,可以的,Spinning Up是OpenAI開(kāi)源的面向初學(xué)者的深度強(qiáng)化學(xué)習(xí)資料,其中列出了105篇深度強(qiáng)化學(xué)習(xí)領(lǐng)域非常經(jīng)典的文章, 見(jiàn) Spinning Up:
博主使用Python爬蟲(chóng)自動(dòng)爬取了所有文章,而且爬下來(lái)的文章也按照網(wǎng)頁(yè)的分類自動(dòng)分類好。
見(jiàn)下載資源:Spinning Up Key Papers
源碼如下:
import os
import time
import urllib.request as url_re
import requests as rq
from bs4 import BeautifulSoup as bf
'''Automatically download all the key papers recommended by OpenAI Spinning Up.
See more info on: https://spinningup.openai.com/en/latest/spinningup/keypapers.html
Dependency:
bs4, lxml
'''
headers = {
'User-Agent':'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/92.0.4515.131 Safari/537.36'
}
spinningup_url = 'https://spinningup.openai.com/en/latest/spinningup/keypapers.html'
paper_id = 1
def download_pdf(pdf_url, pdf_path):
"""Automatically download PDF file from Internet
Args:
pdf_url (str): url of the PDF file to be downloaded
pdf_path (str): save routine of the downloaded PDF file
"""
if os.path.exists(pdf_path): return
try:
with url_re.urlopen(pdf_url) as url:
pdf_data = url.read()
with open(pdf_path, "wb") as f:
f.write(pdf_data)
except: # fix link at [102]
pdf_url = r"https://is.tuebingen.mpg.de/fileadmin/user_upload/files/publications/Neural-Netw-2008-21-682_4867%5b0%5d.pdf"
with url_re.urlopen(pdf_url) as url:
pdf_data = url.read()
with open(pdf_path, "wb") as f:
f.write(pdf_data)
time.sleep(10) # sleep 10 seconds to download next
def download_from_bs4(papers, category_path):
"""Download papers from Spinning Up
Args:
papers (bs4.element.ResultSet): 'a' tags with paper link
category_path (str): root dir of the paper to be downloaded
"""
global paper_id
print("Start to ownload papers from catagory {}...".format(category_path))
for paper in papers:
paper_link = paper['href']
if not paper_link.endswith('.pdf'):
if paper_link[8:13] == 'arxiv':
# paper_link = "https://arxiv.org/abs/1811.02553"
paper_link = paper_link[:18] + 'pdf' + paper_link[21:] + '.pdf' # arxiv link
elif paper_link[8:18] == 'openreview': # openreview link
# paper_link = "https://openreview.net/forum?id=ByG_3s09KX"
paper_link = paper_link[:23] + 'pdf' + paper_link[28:]
elif paper_link[14:18] == 'nips': # neurips link
paper_link = "https://proceedings.neurips.cc/paper/2017/file/a1d7311f2a312426d710e1c617fcbc8c-Paper.pdf"
else: continue
paper_name = '[{}] '.format(paper_id) + paper.string + '.pdf'
if ':' in paper_name:
paper_name = paper_name.replace(':', '_')
if '?' in paper_name:
paper_name = paper_name.replace('?', '')
paper_path = os.path.join(category_path, paper_name)
download_pdf(paper_link, paper_path)
print("Successfully downloaded {}!".format(paper_name))
paper_id += 1
print("Successfully downloaded all the papers from catagory {}!".format(category_path))
def _save_html(html_url, html_path):
"""Save requested HTML files
Args:
html_url (str): url of the HTML page to be saved
html_path (str): save path of HTML file
"""
html_file = rq.get(html_url, headers=headers)
with open(html_path, "w", encoding='utf-8') as h:
h.write(html_file.text)
def download_key_papers(root_dir):
"""Download all the key papers, consistent with the categories listed on the website
Args:
root_dir (str): save path of all the downloaded papers
"""
# 1. Get the html of Spinning Up
spinningup_html = rq.get(spinningup_url, headers=headers)
# 2. Parse the html and get the main category ids
soup = bf(spinningup_html.content, 'lxml')
# _save_html(spinningup_url, 'spinningup.html')
# spinningup_file = open('spinningup.html', 'r', encoding="UTF-8")
# spinningup_handle = spinningup_file.read()
# soup = bf(spinningup_handle, features='lxml')
category_ids = []
categories = soup.find(name='div', attrs={'class': 'section', 'id': 'key-papers-in-deep-rl'}).\
find_all(name='div', attrs={'class': 'section'}, recursive=False)
for category in categories:
category_ids.append(category['id'])
# 3. Get all the categories and make corresponding dirs
category_dirs = []
if not os.path.exitis(root_dir):
os.makedirs(root_dir)
for category in soup.find_all(name='h4'):
category_name = list(category.children)[0].string
if ':' in category_name: # replace ':' with '_' to get valid dir name
category_name = category_name.replace(':', '_')
category_path = os.path.join(root_dir, category_name)
category_dirs.append(category_path)
if not os.path.exists(category_path):
os.makedirs(category_path)
# 4. Start to download all the papers
print("Start to download key papers...")
for i in range(len(category_ids)):
category_path = category_dirs[i]
category_id = category_ids[i]
content = soup.find(name='div', attrs={'class': 'section', 'id': category_id})
inner_categories = content.find_all('div')
if inner_categories != []:
for category in inner_categories:
category_id = category['id']
inner_category = category.h4.text[:-1]
inner_category_path = os.path.join(category_path, inner_category)
if not os.path.exists(inner_category_path):
os.makedirs(inner_category_path)
content = soup.find(name='div', attrs={'class': 'section', 'id': category_id})
papers = content.find_all(name='a',attrs={'class': 'reference external'})
download_from_bs4(papers, inner_category_path)
else:
papers = content.find_all(name='a',attrs={'class': 'reference external'})
download_from_bs4(papers, category_path)
print("Download Complete!")
if __name__ == "__main__":
root_dir = "key-papers"
download_key_papers(root_dir)
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三、微軟北京裁員了嗎
微軟北京裁員了,1、公司的賠償是(N+2)個(gè)月的薪水。
N是你在這個(gè)公司工作的年數(shù)。而這個(gè)薪水和你平時(shí)拿到手里面的不一樣,一般要高出一些。它的計(jì)算方式是你平時(shí)前12個(gè)月收入總和除以12。這個(gè)收入包含你每個(gè)月稅前收入總和,包括住房公積金、醫(yī)療補(bǔ)助、股票、車補(bǔ)、飯補(bǔ)甚至是手機(jī)補(bǔ)助,以及所有過(guò)去12個(gè)月的獎(jiǎng)金,年中雙薪。這樣算下來(lái),如果你的薪水過(guò)萬(wàn)的話,裁員的月薪計(jì)算要兩倍于你的單月稅后。當(dāng)然這個(gè)是公司自己設(shè)定的優(yōu)惠補(bǔ)償,一般大規(guī)模裁員都是這樣。而普通的法律上的規(guī)定也是這么算,但是有一個(gè)限額,北京市大概是1.2萬(wàn)的月薪,超過(guò)這個(gè)就只能按照1.2萬(wàn)去算。所以說(shuō)走法律規(guī)定索賠是很虧的。
N+2的2是個(gè)很彈性的數(shù)字,有的公司是N+1。但是如果不是一個(gè)月提前通知的話,就應(yīng)該多一個(gè)月,也就是+2。不少公司福利好的也有+3+4甚至是+6,都是怕大規(guī)模裁員員工鬧事。另外一點(diǎn)這個(gè)2里面的數(shù)額,是根據(jù)你上一個(gè)月的收入總和來(lái)算的。我比較幸運(yùn)的是上個(gè)月剛發(fā)完獎(jiǎng)金,所以數(shù)額蠻大的。
四、現(xiàn)在游戲里面可以打那個(gè)openAI了嗎
先把你的openal32.dll刪掉,也就是c:;wiindows;system32 文件夾中的openai32.dll和游戲文件夾中的openai32.dll 。然后OpenAL 最后再裝上OpenAL 這就行了。我就是這么解決塵埃3不能玩的~
以上就是關(guān)于openai中國(guó)可以用嗎相關(guān)問(wèn)題的回答。希望能幫到你,如有更多相關(guān)問(wèn)題,您也可以聯(lián)系我們的客服進(jìn)行咨詢,客服也會(huì)為您講解更多精彩的知識(shí)和內(nèi)容。
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